Diagnostic method and diagnostic system for monitoring available resources in a production process

ABSTRACT

The invention relates to a diagnosis method which permits continuous monitoring of the available resources in a production process, into which a number of supply links are incorporated in the form of a network and supply a system provider or other supply links with raw materials, semifinished products, components and services. Each supply link has an input buffer, an output buffer and a process stage, on the basis of the design of which the supply link determines an identification number which characterizes the operating state of this supply link. The predicted demands of the system provider and the current reserves in the buffers of each supply link are used as a basis to calculate—using the identification numbers of the supply links—for each supply link whether its reserves satisfy the predicted demands of the system provider, i.e. whether it is capable of supplying. Deficits in the stocks of a supply link are notified to all the other supply links, so that a high transparency of the current state of the resources in the supply network is achieved without the supply links having to disclose internal matters concerning their processes. The method is suitable in particular for monitoring resources in supply networks into which supply links outside the company are incorporated. This is a decisive difference in comparison with the PPC systems available on market, which do not take into account suppliers and subcontracted suppliers outside the company.

BACKGROUND AND SUMMARY OF THE INVENTION

The invention relates to a diagnosis method and system for monitoringthe available resources in a production process and to a diagnosissystem with the aid of which this method can be implemented.

The production of complex products by a system provider takes place in ahierarchical production process in which a large number of differentresources in the form of raw materials, semifinished products,components and services are required in the successive stages ofproduction. These resources are procured by the system provider fromsupply links, some of which may be in-house suppliers, while others maybe outside suppliers. To avoid capacity shortages in the supplies to thesystem provider, resources in the form of reserves and stocks are keptby the supply links, tying up a considerable proportion of capital. Ifthese stocks become too great, the tied-up capital causes unnecessarycosts. If the stocks become too low, on the other hand, delivery datescannot be met. This is particularly so when there are fluctuations indemand. As a result, losses may arise. There is therefore a great needto optimize the available resources in the production process in such away that the costs associated with them are minimized.

Conventional production planning and control systems deal with thequestions and planning tasks arising during the design of the productionprocess in a cascading procedure. This produces a static appraisal ofthe operations. Successful use of an integrated overall system fordescribing and planning the production process presupposes that all thedata necessary for monitoring the production process can be madeavailable at any time. This requires not only continuous monitoring ofthe reserves and stocks of all the supply links involved in theproduction process, but in particular also data concerning the design ofthe production and logistical processes, capacity utilization etc. ofeach individual supply link.

To obtain a realistic picture of the production process in its entiretyand its behaviour when fluctuations in demand occur, the individualsteps must be treated as parts of an integrated system which includesthe complete production process. Such a planning and diagnosis system,with the aid of which a complex production process can be planned andconstantly kept up-to-date for applications within a single company isknown, for example, from WO 98/08177.

If, however, the production process also includes legally independentsuppliers operating freely in the market, data which can be continuouslycalled up concerning capacity utilization, production and logisticalprocesses etc. of the supplier are generally not available. Thisinformation forms part of the core know-how of the supplier, whichoutside parties, in particular other suppliers or competitors—are notpermitted to view. Consequently, existing overall systems for describingand planning the production process can be meaningfully used only forplanning within a single company, and the systems will fail if they aredistributed among different parties within different companies and ifoutside suppliers are incorporated.

Therefore, it is an object of the invention to propose a diagnosismethod which permits continuous monitoring of the available resources ina production process in which outside supply links are incorporated.Furthermore, it is an object of the invention to provide a diagnosissystem with which this diagnosis method can be implemented.

Accordingly, the entire network of supply links involved in theproduction process is replicated in its complexity, with the associatedlead times for each individual supply link, in a diagnosis system. Thediagnosis system also contains continuously updated data concerning thepredicted gross demands and a demand forecast of the system provider,information on the current reserves and stocks of each individual supplylink and, for each supply link, an identification number, which is ameasure of the responsiveness of the supply link to changes in thedemands of the system provider. The diagnosis system in this casereplicates a production system operating on the “pull principle”, inwhich the demands of the system provider form the trigger for the entireproduction chain—and consequently also for each individual supply link.

The predicted demands of the system provider and the informationconcerning the current reserves and stocks of each supply link are usedas a basis to calculate in the diagnosis system whether the currentstocks of the supply link concerned are sufficient for the predicteddemands of the system provider. The calculation uses the identificationnumber of the supply link. The results of this calculation are availableat any time to all the supply links —together with the structure and allthe lead times of the entire network of supply links. Consequently, eachsupply link receives from the diagnosis system information on whichamounts of the goods provided by it are required at which point in timeby the system provider or by other supply links. On the other hand, thesupply link learns at which points in the network capacity shortageshave occurred and consequently has the possibility of adjusting its owncapacities (stocks, capacity utilization etc.) accordingly. For example,if it can see in advance that another supply link, supplying to it,cannot provide the required amounts of raw material, the supply link canpossibly look around in time for an alternative supplier. Or the supplylink can establish that shortages exist in the case of another supplylink, downstream in its supply chain, and this supply link will requestlower sales volumes from the other supply link on the basis of the pullprinciple, and can cut back its own capacity in time. Each supply linkcan consequently detect shortages and help in advance to eliminate them.The supply link can also use this information to optimize its stocks,which for the most part result from inadequately coordinated capacities.Since stocks kept by supply links are synonymous with multiple storageof products at different value-adding stages, considerable savings canconsequently be achieved in the entire production process.

By simultaneously providing all the information relevant to the systemprovider and the supply links in the diagnosis system, information flowsboth in the forward direction and in the backward direction are possiblein the network of supply links. The diagnosis system consequently hasthe function of an early-warning system in the short-term andmedium-term periods, allowing all those involved in the network torespond appropriately and timely to local disruptions in the productionprocess. Furthermore, all changes in demand and stocks (for example inthe stocks of a supply link) can be fed directly by the system providerand the supply links online into the diagnosis system and consequentlycan notify simultaneously all those involved in the production system.This allows phasing-out costs when a model is discontinued to beminimized. Furthermore the launch of a new model on the productionsystem can take place in parallel with models already in productionwithout great additional effort.

A particularly concise way of representing the supply capability of eachsupply link is achieved by using a traffic-light function, in which asupply link is given a “green light” if the stocks kept by this supplylink correspond at least to the predicted demand, whereas the supplylink is given a “red light” if its stocks are below the predicteddemand.

To allow an uninterrupted information flow on the current standing ofthe supply chain to be ensured, even in the event of a data failure of asupplier, a lead time is expediently determined in advance for eachsupply link. The lead is the time interval between the incoming-goods oroutgoing-goods point of this supply link and the assembly site of thesystem supplier. This is because, irrespective of the provision of dataconcerning current stocks by the supply links, it is possible on thebasis of the demands of the system provider to calculate, using the leadtime at any point in time the amounts of reserves, semifinished productsetc. which should be present in the stores of the supply links at thispoint in time.

It is also expedient to use an interpreter list to reference theintermediates supplied by the supply links to the end product producedby the system provider. This interpreter list ensures the “translation”between the nomenclatures of parts of the supply links and thedesignation of parts used by the system provider, and ensures that eachsupply link is informed as to the amounts and types of raw materials andintermediates to be supplied by it, from which the end product isproduced by the system provider.

The diagnosis system is expediently accessed via the Internet. In thisway it can be ensured that supply links around the world can view thecurrent status of the network at any time and can themselves feed theircurrent data into the information system.

The diagnosis system consequently ensures the greatest possibletransparency of the entire production process and the resources of allthe supply links involved in it, since it is possible for outside supplylinks to obtain company-internal parameters for themselves at the sametime. Although the supply link must specify an identification number,which is a measure of its supply capability (and consequently at leastindirectly contains internal process and capacity utilization data), thedetermination of this identification number is left to each individualsupply link itself. The supply link can consequently make known itssupply capability and supply readiness by the choice of itsidentification number and at the same time retains the greatest possibleautonomy.

A range, which is a measure of the time period over which the supplylink is capable of balancing out fluctuations in demand of the systemprovider, is expediently chosen as the identification number of thesupply link. If the supply link indicates a very small range for itssupply capability, and consequently presents itself as very “agile”, itindicates by this that it can very rapidly adapt its process stage tochanged demands of the system provider. However, this involves the riskof the supply link having supply problems if there are strong ormedium-term fluctuations in the demand of the system provider, which isexpressed by a “red” traffic light. If, on the other hand, the supplylink indicates a very large range for its supply capability, thissuggests that the supply link has large stocks, which it can use tobalance out fluctuations in demand. Consequently, its traffic lightremains “green” even when there are large changes in the demand of thesystem provider, but it must be assumed, in particular if ranges areexceedingly high, that the supply link has overdimensioned its store andis consequently keeping considerable dead capital.

Observing the traffic lights, and consequently monitoring the output ofthe diagnosis method, over a certain period of time therefore gives boththe system provider and the supply links valuable indications as towhether, and to what extent, process stages and storage capacities ofthe supply links can be optimized, in order to ensure a satisfactorysupply capability with the lowest possible storage costs. An importantaspect here is that, in the diagnosis method according to the invention,the system provider primarily assumes the role of an observer and, inparticular, need not assume any responsibility for the smooth operationof the supply chain. Only the structure of the supply network andcontinuously updated values for the predicted demand figures areprovided to the system provider regulating the stocks kept by the supplylinks is then the responsibility of the supply links themselves. This isan important prerequisite for working together with legallyindependently operating companies. The diagnosis method consequentlydescribes a self-regulating system in which the supply links choose, onthe basis of information made available to them in the diagnosis systemby the system provider and the other supply links, their own “optimumoperating state” and consequently contribute to the optimization of theentire supply chain. In particular, no optimization of the entire supplynetwork is carried out by the system provider. Such wide-rangingoptimization would mean a far-reaching intervention into the autonomy ofthe supply links and would consequently be unacceptable to the majorityof the supply links.

However, the diagnosis system allows the system provider to carry outcontinuous monitoring of shortages in stocks and in particular insupplies in the network of the supply links. Consequently, impendingsupply shortages among subcontracted suppliers can be detected in theshort and medium terms. An early response to the shortages increases thedelivery capability of the supply chain overall.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is explained below on the basis of an exemplary embodimentrepresented in the drawings, in which:

FIG. 1 shows a schematic representation of a network of supply linksinvolved in a production process,

FIG. 2 shows a selected supply chain in the network of the supply links,

FIG. 3 shows a representation of the predicted demand of a systemprovider and the resultant desired stocks which must be kept by thesupply links.

DETAILED DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a representation of a production process, in which rawmaterials, semifinished products and system components from which an endproduct is produced by a system provider 3, are provided by a network 1of supply links 2. Each supply link 2 in this network 1 is representedin FIG. 1 in the form of a small box; the arrows between the boxesindicate the direction of supply between the supply links 2. The term“supply link” refers here not only to production plants for rawmaterials, semifinished products or system components, but also toservice providers, such as transport agents 4 for example (the boxes ofwhich are shown with a light-grey background in FIG. 1). The supplylinks 2 jointly supply to the system provider 3, which represents thefinal link of the network 1. The majority of the supply links 2 withinthe network 1 are interconnected in a manner in which they are dependenton one another in the form of supply chains 5. A supply link 2 suppliesgoods to the supply link 2′ following it in the supply sequence. Anexample of supply links 2 which together represent such a supply chain 5is shown hatched in FIG. 1.

FIG. 2 shows an actual example of a supply chain 5 including a pluralityof supply links 2. This example concerns the production process ofleather components, which are assembled by the system provider 3 as partof a door lining of a car. The supply chain 5 comprises three productionplants 6, 7, 9, two of which production plants 6 (cutting leather tosize) and 7 (sewing leather) are located in South Africa, and oneproduction plant 9 (door lining part-assembly) is located in Germany.Furthermore, the supply chain 5 includes a transport company 8, whichtransports the semifinished leather products from South Africa toGermany. As shown in FIG. 2, each supply link 2 has an input buffer 10,an output buffer 11 and a process stage 12, which may comprise one ormore stages of production, transport stages etc. The buffers 10, 11represent stocks and serve the purpose of at least partly decoupling thematerial flow between the other supply links 2 located in the supplychain 5. For example, the input buffer 10′ of the production plant 9ensures that the production plant 9 has sufficient semifinished leatherproducts available for the part-assembly of the door lining until thenext delivery is made. To be able to assemble door linings even whenthere are supply difficulties at the production plants 6 and 7 or thetransport agent 8, it may be advisable for the production plant 9 tomake its input buffer 10′ larger. The size of the input buffer 10′ ofthe production plant 9 is consequently dependent to a great extent onhow well the production plant 9 is informed about the current state ofthe production plants 6, 7 and the transport agent 8 supplying to it.The output buffer 11′ of the production plant 9 on the other handensures that the production plant 9 has sufficient part-assembled doorlinings available to supply to the system provider 3 even when there aredifficulties in its own process stage 12′ or if there is an increaseddemand by the system provider 3.

To produce a certain number of the end products, the system provider 3requires a certain amount of the goods or services supplied in time bythe supply links 2. The demands of the system provider 3, in their timesequence projected into the future, are encoded, according to the “pullprinciple,” into demands with respect to each individual supply link 2in the network 1. To calculate the demands of each individual supplylink 2, a certain percentage of waste must be taken into account, atleast for some supply links 2 of a supply chain 5, on account ofinadequate quality. The gross demands of the supply links 2 aretherefore generally higher than those demands which would result from anaive calculation back from the demands of the system provider 3. Inaddition, the further away from the end stage of the system provider 3the supply link 2 is in the supply chain 5, the higher the gross demand.

To calculate the gross demands with respect to each supply link 2, leadtimes, caused for example by the process stages of the supply links 2,must be taken into account. FIG. 3 shows a diagram of the predicteddemands of the system provider 3 with respect to a specific supply link2′ in its time sequence. B₀ designates here the amount of thesemifinished product provided (at an earlier point in time) by supplylink 2′, which is being assembled at the current point in time t₀ by thesystem provider 3. If δ designates the lead time of the supply link 2′in the supply chain 5, the supply link 2′ must be able at the presentpoint in time t₀ to supply an amount B₁ of the semifinished product toallow the demand of the system provider 3 for semifinished product (orthe components provided from it by other supply links) to be covered atthe later point in time t₁=t₀+δ. The lead time δ of the supply link 2′corresponds to the average time interval between the outgoing-goodspoint at the supply link 2′ and the assembly site at the system provider3′.

The gross demand B₁ is used to determine for the supply link 2′ adesired stock, which must be available at the current time t₀ in theoutput buffer 11′ of the supply link 2′ in order to supply properly tothe supply chain 5, and consequently ultimately also to the systemprovider 3. This calculation is performed using the range T of thesupply link 2′. The range T is in this case a supply-link-dependentparameter, which each individual supply link 2′ determines or estimatesfor itself on the basis of its internal process and storage capacities.

The desired stock in the output buffer 11′ of the supply link 2′ is thencalculated from the total of all the gross demands to be expected in thetime period between t₁ and t₁+T:desired  stock = ∫_(t₁)^(t₁ + T)gross  demand 

This desired stock is shown with a gray background in FIG. 3.

If the momentary stock of the output buffer 11′ of the supply link 2′ isless than the desired stock, there is the risk of the supply link 2′being unable at the time t₀ to satisfy the demands B₁ required by thesystem provider at the time t₁=t₀+δ. Such a discrepancy is covered by a“warning function”, whereas an actual stock exceeding the desired stockis referred to as “in order”. The range T, by which the supply link 2′characterizes its own buffering and process capacities, consequently hasthe meaning of a “response time”. If the supply link 2′ has a processstage 12′ with a variable capacity and consequently can be adjustedquickly to fluctuations in demand, the supply link 2′ can characterizeitself by a small range T. This is because it is then possible tocompensate for a large part of a (time-limited) increase in demand by atemporarily increased utilization of the capacity of the process stage12′ (for example of production), and only a small part of the outputbuffer 11′ is in this case emptied to meet the increased demand. If, onthe other hand, the supply link 2′ has a slow-responding process stage12′, fluctuations in demand can only be balanced out with a great timedelay. Such a supply link 2′ must therefore set up a correspondinglylarge output buffer 11′, to be able to supply at any time the requiredgross demands in time, even if there are fluctuations in demand.

The range T, to be set by each supply link 2′ itself, is consequently ameasure of the time period over which the supply link 2′ is capable ofbalancing out fluctuations in demand. If the supply link 2′ chooses along range T, the gross demands are averaged over a long time period Tto calculate the desired stock of the output buffer 11′. In this way,fluctuations in demand are averaged out.

By analogy with the determination of the range T for the output buffer11′, a range T′ can also be determined for the input buffer 10′ of thesupply link 2′, used for calculating the desired stock of the inputbuffer 10′.

Provided for the continuous monitoring of the supply capability of theentire network 1 of the supply links 2 is a diagnosis system 13, shownwith broken lines in FIG. 2. This diagnosis system 13 contains all theinformation concerning the interconnection of the supply links 2 and theranges T, T′ of all the supply links 2. In addition, the lead times δ ofsupply links 2 are stored in the diagnosis system 13. Further, thediagnosis system 13 contains current data concerning the predicteddemands of the system provider 3 and the stocks of the buffers 10, 11 ofall the supply links 2. These data are continuously kept up-to-date. Inthe diagnosis system 13, the supply capability of each individual supplylink 2 is continuously determined from the current demand and stock databy using the ranges T, T′ of the supply links 2 regardless whether ornot the stocks of the buffers 10, 11 of the supply link 2 exceed thepredicted demands.

Each supply link 2 in the network 1 is notified of the result of thischeck, and the accompanying “warning function”. This is indicated inFIG. 2 by the broken arrows, which link the diagnosis system 13 to eachsupply link 2. Each supply link 2 consequently receives from thediagnosis system 13 data/information concerning (potential) supplyincapabilities of the other supply links 2 in the network 1. It is thenthe responsibility of the supply link 2 to determine the consequencesfrom this overall information to adapt its own buffers 10, 11 or processstages 12 and/or to take corresponding action with respect to othersupply links 2 on which it depends. No planning interventions in theindividual plans of the supply links 2 take place from the systemprovider 3, so that the planning sovereignty of each individual supplylink 2 is preserved.

Since the lead times δ of all the supply links 2 are replicated in thediagnosis system 13, each supply link 2′ can view the lead times δ ofall the other supply links 2. Consequently, the diagnosis system makesthe lead times δ and their dependencies on one another transparent forall the supply links 2. If, for example, because of a data failure, oneof the supply links 2′ cannot supply any data concerning its buffers 10,11, the volumes to be supplied can nevertheless be calculated on thebasis of the lead times δ and the demands of the system provider 3 forall the other supply links 2 and made available to these supply links 2.Even in the event of a (local) data failure, the “warning function”therefore operates for all the other supply links 2.

The diagnosis system 13 is expediently implemented as a data processingprogram on a central computer. The central computer is located forexample at the site of the system provider 3, and the supply links 2expediently access the diagnosis system 13 via the Internet. To ensurethat only current supply links 2, involved in the supply network 1, canview the diagnosis system 13 and have rights to enter data on it, accessto the Internet page concerned is protected by a password.

The discrepancies between the demand and the stock kept by a supply link2 are expediently visually presented in the diagnosis system 13 in theform of a traffic-light function. Accordingly, the input and outputbuffers 10, 11 of each supply link 2 are allocated a traffic light,which can indicate the colors green (for “demand and stocks match”) orred (for “demand and stocks are in disparity”). Every supply link 2 cantherefore see from the diagnosis system 13 whether and to what extentthe supply links 2 ahead of it in the supply chain 5 are capable ofmeeting future demands. At the same time, the diagnosis system 13 allowsthe system provider 3 to check along the entire supply network 1 whetherthe necessary goods can be provided on time by the supply links 2.Furthermore, the traffic-light function offers the supply links 2reference points for the design of their buffers 10, 11. If the trafficlight of a supply link 2 is constantly at “green”, the current stockkept by this supply link is continuously above the desired stock. Thebuffers 10, 11 of this supply link 2 have therefore possibly been chosento be too large. In this case, this supply link 2 can achieveconsiderable cost savings by a reduction in its buffers 10, 11. If,however, the traffic lights of many supply links 2 are noticeably oftenat “red” in one branch 5 of the network 1, this indicates problems ofthe supply links or could be an indication of an incorrect estimation ofthe lead times d. In this case, a careful analysis of the dependencieson one another of the supply links 2 in this branch 5 is recommended.

The reference between the goods to be supplied on the part of a supplylink 2 (raw materials, semifinished products) and the end product of thesystem provider is expediently replicated by using an interpreter list.For example, for the production of a door lining which bears the partnumber “13687.99” at the system provider 3, one large cut-to-size pieceof leather and three identical small cut-to-size pieces of leather arerequired as supplied parts. These cut-to-size pieces of leather aredesignated at the supply link 2 by the part numbers “LZ 3458-7” and “LZ3469-2”. The interpreter list consequently contains the informationthat, to produce each door lining, one part with the number “LZ 3458-7”and three parts with the number “LZ 3469-2” of the supplier 2 arerequired, and these are jointly allocated to the end product with thenumber “13687.99” of the system provider 3. The interpreter listconsequently contains the complete information on the construction ofthe end product of the system provider 3 from the raw materials,semifinished products and intermediates made available by the supplylinks 2. The interpreter list forms part of the diagnosis system 13 andallows the exact encoding of the goods and services which are necessaryfor the production of the end product.

Up to now a description has been given of the case of an interconnectedsupply chain 5 in which the supply links 2 supply sequentially in strictdependence. However, the network 1 of the supply links is generallynon-linear, as represented in FIG. 1, so that a supply link 2 issupplied by a number of other supply links 2. Furthermore, a supply link2 (for example a forwarding agent) may also be represented a number oftimes in a single supply chain and/or may be represented simultaneouslyin a number of different supply chains 5 (for example supply link 4 inFIG. 1). In this case, the supply link 2 must optimize (internally) thedesign of all the buffers 10, 11 and the capacity utilization of all itsprocess stages 12 in a way such that it is capable of satisfyingsimultaneously all the demands placed on it by the system provider 3.Finally, the semifinished products provided by a supply link may also beassembled on the part of the system provider 3 at a number of differentproduction sites 3′, so that, as represented by broken lines in FIG. 1,the semifinished products are delivered not only to the system provider3 itself, but also to other sites 3′.

1. Diagnosis method for monitoring the available resources in aproduction process with supply links, which comprise in particularproduction plants and/or service providers, in which components aresupplied by a number of supply links to a system provider, which putsthese components together to form a system, in which any number ofsupply links are situated in relation to one another in aninterconnected supply chain, so that they are in turn supplied by othersupply links, each supply link having an input buffer, an output bufferand a process stage, the diagnosis method comprising the steps thatfirstly an identification number is determined for each supply stage onthe basis of the design of its buffers and its process stage, thatinformation concerning the predicted demands of the system provider intheir time sequence is made available by the system provider continuallyover time to each supply link, that information concerning the momentarystock of its buffers is supplied continually over time by each supplylink, that the identification numbers of the supply links are used todetermine continually over time whether their momentary buffer stockssatisfy the predicted demands of the system provider, and that theresults of this assessment are made available continually over time tothe supply links.
 2. Diagnosis method according to claim 1, wherein theidentification number of a supply link is determined by this supply linkitself.
 3. Diagnosis method according to claim 1, wherein the results ofthis assessment are made available to the supply links in the form of atraffic-light function.
 4. Diagnosis method according to claim 1,wherein a range, which is a measure of the time period over which thesupply link is capable of balancing out demand fluctuations of thesystem provider, is chosen as the identification number for thedetermination of the supply capability of the supply link.
 5. Diagnosismethod according to claim 1, wherein a lead time δ, which corresponds tothe time interval between the input buffer or output buffer of thesupply link and the input buffer of the system provider, is determinedfor each supply link.
 6. Diagnosis method according to claim 1, whereinan interpreter list, which contains the reference of the intermediatesproduced by the particular supply link to the end product of the systemprovider, is created for each supply link.
 7. Diagnosis system formonitoring the available resources in a production process, a network ofsupply links (2, 2′, 4) which supply to a system provider being involvedin the production process, each supply link having an input buffer, anoutput buffer and a process stage, and any number of the supply linksbeing situated in relation to one another in an interconnected supplychain, the diagnosis system replicating the interconnection of thesupply links with respect to one another, and also containing dataconcerning predicted demands of the system provider and alsoidentification numbers and data concerning momentary buffer stocks ofall the supply links, wherein each supply link's identification numberis determined on the basis of the design of its buffers and its processstage, and it being possible for the data contained in the diagnosissystem to be called up by the system provider and all the supply links.8. Diagnosis system according to claim 7, wherein the diagnosis systemis accessible to the supply links via the Internet.
 9. A diagnosismethod for monitoring available resources in a production process, theproduction process including a system provider and a plurality of supplylinks that supply components to the system provider for assembly into asystem, the supply links being placed in an interconnected supply chain,each supply link having an input buffer, an output buffer and a processstage, the diagnosis method comprising: providing an identificationnumber for each supply link on the basis of the design of its buffersand its process stage; the system provider providing to each supply linkinformation concerning the predicted demands of the system provider as afunction of time; each supply link providing information concerning themomentary stock of the supply link's buffers; determining whether eachsupply link's momentary buffer stocks satisfies the predicted demands ofthe system provider, using the identification number of the supply link;and providing to the supply links the results of determining whethereach supply link's momentary buffer stocks satisfies the predicteddemands of the system provider.
 10. The diagnosis method according toclaim 9, wherein each supply link determines its own identificationnumber.
 11. The diagnosis method according to claim 9, furthercomprising providing to the supply links, in the form of a traffic-lightfunction, the results of determining whether each supply link'smomentary buffer stocks satisfy the predicted demands of the systemprovider.
 12. The diagnosis method according to claim 9, wherein eachsupply link's identification number is a range, which is a measure ofthe time period over which the supply link is capable of balancing outdemand fluctuations of the system provider.
 13. The diagnosis methodaccording to claim 9, further comprising determining a lead time (δ) foreach supply link, which lead time corresponds to a time interval betweenthe input buffer or output buffer of the supply link and the inputbuffer of the system provider.
 14. The diagnosis method according toclaim 9, further comprising creating an interpreter list for each supplylink, which list links intermediary products produced by the supply linkto an end product of the system provider.
 15. A diagnosis system formonitoring the available resources in a production process thatincludes: a system provider; a network of supply links which supply tothe system provider, each supply link including: an input buffer, anoutput buffer, and a process stage; and a supply chain including anumber of the interconnected supply links, the diagnosis systemcomprising: a replication of the interconnection of the supply links;data concerning predicted demands of the system provider; identificationnumbers for the supply links, wherein each supply link's identificationnumber is provided on the basis of the design of its buffers and itsprocess stage; and data concerning momentary buffer stocks of the supplylinks, wherein the data contained in the diagnosis system are accessibleby the system provider and the supply links.
 16. The diagnosis systemaccording to claim 15, wherein the diagnosis system is accessible to thesupply links via the Internet.